Since then, with applied math, a Ph.D., etc. getting a job has been a scavenger hunt.
A good background in stochastic processes was supposed to be good for a career on Wall Street, but Goldman Sachs and Morgan Stanley didn't agree.
I'm no longer looking for a job. Instead I'm starting a business and now am quite far along. I may have a nice stream of revenue later this year.
Yes, for this thread, a background in parts of control theory might help in work in robotics. But some of the other considerations remain: Will the hiring manager be comfortable with a subordinate who knows more? Will the HR people recognize good qualifications when they see them? Is it really good to recommend to a young person to study control theory on some possibility that it will help getting a job in robotics?
There is a bigger issue that I omitted: Math in the US is still dominated by 'pure math' (some of which is crucial) which as a field is still mostly interested in "the analytic algebraic topology of the locally Euclidean metrization of infinitely dfferentiable Riemannian manifolds" (an old joke, extra credit for knowing the source), etc. and just HATES any suggestion of 'professional' education. Moreover those academic departments don't have even a weak little hollow hint of a tiny clue about applications outside of pure math or math physics. The pure math departments worked hard to push out probability, statistics, stochastic processes, optimization, control theory, continuum mechanics, numerical methods, graph theory, etc. Yes, there have been some exceptions at Brown and Courant. Yes, for some years there were efforts in 'the mathematical sciences'.
So, in particular, in business, they will take seriously professional work by lawyers and accountants but not mathematicians (main exception, actuaries in insurance). Part of the difference is that lawyers have a rule that a lawyer working as a lawyer can be supervised only by another lawyer. Net, math just has no 'professional' status in business, and that is a big problem for math helping a career in business.
Eventually there was the David Report that claimed that pure math just was not well enough connected with applications to be very relevant, and the NSF then started cutting back on grants for US pure math.
Science, engineering, computer science, statistics in the social sciences, etc. have had to do their own math and generally have done it poorly. It's a bad situation.
Net, for this thread, for a person planning their career, the video was not good; for all the potential math has, a person who pursues math in business will be mostly out on their own; the math will be in some secret sauce that neither the customers nor the venture partners know about.